no code implementations • 26 Nov 2023 • Shubham Kumar Bharti, Stephen Wright, Adish Singla, Xiaojin Zhu
The goal of the teacher is to teach a realizable target policy to the learner using minimum number of state demonstrations.
1 code implementation • 18 Nov 2022 • Shubham Kumar Bharti, Xuezhou Zhang, Adish Singla, Xiaojin Zhu
Instead, our defense mechanism sanitizes the backdoor policy by projecting observed states to a 'safe subspace', estimated from a small number of interactions with a clean (non-triggered) environment.
no code implementations • 16 Jun 2020 • Xuezhou Zhang, Shubham Kumar Bharti, Yuzhe ma, Adish Singla, Xiaojin Zhu
Our TDim results provide the minimum number of samples needed for reinforcement learning, and we discuss their connections to standard PAC-style RL sample complexity and teaching-by-demonstration sample complexity results.
no code implementations • 12 Dec 2019 • Karthikeyan K, Shubham Kumar Bharti, Piyush Rai
Despite the effectiveness of multitask deep neural network (MTDNN), there is a limited theoretical understanding on how the information is shared across different tasks in MTDNN.